News, tutorials, and updates from the Potato team.
Potato 2.3.0 introduces agentic annotation with 12 trace format converters, Solo Mode for human-LLM collaborative labeling, Best-Worst Scaling, SSO/OAuth, Parquet export, and 15 demo projects.
Learn how to set up human evaluation of AI agent outputs using Potato's agentic annotation features, from trace import to annotation schema design.
Step-by-step tutorial on using Potato's Solo Mode to efficiently label large datasets with human-LLM collaboration, reducing annotation cost by up to 90%.
How to use Potato's web agent trace display to evaluate autonomous web browsing agents, with step-by-step screenshots, SVG overlays, and per-step annotation schemas.
Potato 2.2.0 adds 9 new annotation schemas, a pluggable export system, MACE competence estimation, 55 validated survey instruments, and remote data sources.
Potato 2.1.0 brings the instance display system, visual AI support for image and video annotation, span linking, multi-field spans, and layout customization.
Set up AI-powered object detection, pre-annotation, and classification for image and video tasks with YOLO, Ollama, OpenAI, and Claude.
Step-by-step guide for manually converting Label Studio projects, templates, and annotations to Potato format.
Complete guide to integrating Potato with Prolific for crowdsourced annotation, including payment and quality control.
Specialized techniques for annotating contracts, court documents, and regulatory filings with domain expertise.
Best practices for annotating medical images using Potato's standard image annotation features.
How to configure polygon drawing tools for image segmentation, with tips for complex shapes and overlapping regions.
How to use uncertainty sampling to prioritize annotations and reduce the total labeling effort by up to 50%.
Complete guide to setting up bounding box annotation for computer vision tasks, including label colors and validation.
How to convert your Potato annotations into Hugging Face dataset format for model training and sharing.
Build side-by-side image comparison interfaces for preference ranking, A/B testing, and quality assessment.
We're excited to announce Potato 2.0 with AI-powered features, multimedia support, and active learning capabilities.
Configure AI-powered keyword highlighting to draw annotator attention to important terms and phrases.
Step-by-step instructions for running Potato annotation tasks on MTurk with qualification tests and approval workflows.
Build a complete sentiment classification task with radio buttons, tooltips, and keyboard shortcuts for efficient labeling.
Configure Potato for toxicity detection, hate speech classification, and sensitive content labeling with annotator wellbeing in mind.
Create custom annotation interfaces with HTML templates, CSS styling, and JavaScript interactivity.
Build a language learning annotation task for rating pronunciation quality with audio playback and Likert scales.
Build a speaker identification task with audio waveforms, timestamp markers, and speaker label assignment.
Set up video annotation tasks with precise frame navigation, timestamp markers, and temporal event labeling.
Set up annotation for detecting specific sounds like speech, music, applause, or environmental noises with timestamp spans.
A quick guide to setting up your first annotation project with Potato, from installation to your first labeled data.
How to calculate and interpret Cohen's Kappa, Fleiss' Kappa, and Krippendorff's Alpha for your annotation projects.
Our paper on Potato was accepted at EMNLP 2022. Learn about the research behind the tool and how to cite it in your work.
Best practices for ensuring annotation quality in annotation projects, including practical strategies you can implement with and beyond Potato.
Learn how to set up image classification tasks with thumbnail previews, zoom controls, and multi-label support.
Learn how to use OpenAI, Claude, or Gemini to provide intelligent hints and suggestions to your annotators.
Create a music annotation task with waveform visualization, 30-second previews, and hierarchical genre labels.
Production deployment guide for Potato including Docker, cloud platforms, and SSL configuration.
An overview of multi-object tracking annotation concepts and how Potato's video annotation capabilities can support basic tracking workflows.
Create an audio emotion classification task with waveform display, playback speed controls, and Likert scales.
Step-by-step tutorial on creating a named entity recognition annotation task with span labels and keyboard shortcuts.
A deep dive into JSON and JSONL data formats, with examples for text, image, audio, and multimodal annotation.
Configure waveform visualization, playback controls, and text correction interfaces for audio transcription tasks.
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